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This work summarizes the results of the largest skin image analysis challengein the world, hosted by the International Skin Imaging Collaboration (ISIC), aglobal partnership that has organized the world's largest public repository ofdermoscopic images of skin. The challenge was hosted in 2018 at the MedicalImage Computing and Computer Assisted Intervention (MICCAI) conference inGranada, Spain. The dataset included over 12,500 images across 3 tasks. 900users registered for data download, 115 submitted to the lesion segmentationtask, 25 submitted to the lesion attribute detection task, and 159 submitted tothe disease classification task. Novel evaluation protocols were established,including a new test for segmentation algorithm performance, and a test foralgorithm ability to generalize. Results show that top segmentation algorithmsstill fail on over 10% of images on average, and algorithms with equalperformance on test data can have different abilities to generalize. This is animportant consideration for agencies regulating the growing set of machinelearning tools in the healthcare domain, and sets a new standard for futurepublic challenges in healthcare.

Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)